Overview

Dataset statistics

Number of variables47
Number of observations229
Missing cells2713
Missing cells (%)25.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory90.5 KiB
Average record size in memory404.6 B

Variable types

Categorical21
Text7
DateTime3
Unsupported7
Numeric7
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-19975/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신일자 is highly imbalanced (69.6%)Imbalance
업태구분명 is highly imbalanced (68.7%)Imbalance
위생업태명 is highly imbalanced (62.9%)Imbalance
사용끝지하층 is highly imbalanced (62.0%)Imbalance
발한실여부 is highly imbalanced (67.1%)Imbalance
건물소유구분명 is highly imbalanced (79.4%)Imbalance
여성종사자수 is highly imbalanced (76.1%)Imbalance
남성종사자수 is highly imbalanced (83.0%)Imbalance
회수건조수 is highly imbalanced (51.6%)Imbalance
침대수 is highly imbalanced (54.4%)Imbalance
인허가취소일자 has 229 (100.0%) missing valuesMissing
폐업일자 has 38 (16.6%) missing valuesMissing
휴업시작일자 has 229 (100.0%) missing valuesMissing
휴업종료일자 has 229 (100.0%) missing valuesMissing
재개업일자 has 229 (100.0%) missing valuesMissing
전화번호 has 21 (9.2%) missing valuesMissing
도로명주소 has 156 (68.1%) missing valuesMissing
도로명우편번호 has 158 (69.0%) missing valuesMissing
좌표정보(X) has 70 (30.6%) missing valuesMissing
좌표정보(Y) has 70 (30.6%) missing valuesMissing
건물지상층수 has 113 (49.3%) missing valuesMissing
사용시작지상층 has 130 (56.8%) missing valuesMissing
사용끝지상층 has 205 (89.5%) missing valuesMissing
욕실수 has 121 (52.8%) missing valuesMissing
발한실여부 has 14 (6.1%) missing valuesMissing
조건부허가신고사유 has 229 (100.0%) missing valuesMissing
조건부허가시작일자 has 229 (100.0%) missing valuesMissing
조건부허가종료일자 has 229 (100.0%) missing valuesMissing
다중이용업소여부 has 14 (6.1%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 100 (43.7%) zerosZeros
사용시작지상층 has 84 (36.7%) zerosZeros
사용끝지상층 has 9 (3.9%) zerosZeros
욕실수 has 84 (36.7%) zerosZeros

Reproduction

Analysis started2024-05-11 08:49:12.421423
Analysis finished2024-05-11 08:49:14.554454
Duration2.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3230000
229 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 229
100.0%

Length

2024-05-11T08:49:14.891186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:15.373039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 229
100.0%

관리번호
Text

UNIQUE 

Distinct229
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-11T08:49:15.949466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5038
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique229 ?
Unique (%)100.0%

Sample

1st row3230000-202-1969-00223
2nd row3230000-202-1973-00224
3rd row3230000-202-1976-00222
4th row3230000-202-1976-00225
5th row3230000-202-1976-00226
ValueCountFrequency (%)
3230000-202-1969-00223 1
 
0.4%
3230000-202-2002-00012 1
 
0.4%
3230000-202-2003-00030 1
 
0.4%
3230000-202-2003-00031 1
 
0.4%
3230000-202-2003-00032 1
 
0.4%
3230000-202-2003-00033 1
 
0.4%
3230000-202-2003-00034 1
 
0.4%
3230000-202-2003-00035 1
 
0.4%
3230000-202-2003-00036 1
 
0.4%
3230000-202-2003-00037 1
 
0.4%
Other values (219) 219
95.6%
2024-05-11T08:49:17.283832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2048
40.7%
2 941
18.7%
- 687
 
13.6%
3 599
 
11.9%
1 233
 
4.6%
9 176
 
3.5%
8 96
 
1.9%
6 73
 
1.4%
4 70
 
1.4%
7 62
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4351
86.4%
Dash Punctuation 687
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2048
47.1%
2 941
21.6%
3 599
 
13.8%
1 233
 
5.4%
9 176
 
4.0%
8 96
 
2.2%
6 73
 
1.7%
4 70
 
1.6%
7 62
 
1.4%
5 53
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 687
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5038
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2048
40.7%
2 941
18.7%
- 687
 
13.6%
3 599
 
11.9%
1 233
 
4.6%
9 176
 
3.5%
8 96
 
1.9%
6 73
 
1.4%
4 70
 
1.4%
7 62
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5038
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2048
40.7%
2 941
18.7%
- 687
 
13.6%
3 599
 
11.9%
1 233
 
4.6%
9 176
 
3.5%
8 96
 
1.9%
6 73
 
1.4%
4 70
 
1.4%
7 62
 
1.2%
Distinct136
Distinct (%)59.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1969-09-19 00:00:00
Maximum2023-02-06 00:00:00
2024-05-11T08:49:17.769904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:49:18.414928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3
191 
1
38 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 191
83.4%
1 38
 
16.6%

Length

2024-05-11T08:49:19.018685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:19.581914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 191
83.4%
1 38
 
16.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
폐업
191 
영업/정상
38 

Length

Max length5
Median length2
Mean length2.4978166
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 191
83.4%
영업/정상 38
 
16.6%

Length

2024-05-11T08:49:20.114752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:20.552368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 191
83.4%
영업/정상 38
 
16.6%
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2
191 
1
38 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 191
83.4%
1 38
 
16.6%

Length

2024-05-11T08:49:20.998982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:21.297554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 191
83.4%
1 38
 
16.6%
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
폐업
191 
영업
38 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 191
83.4%
영업 38
 
16.6%

Length

2024-05-11T08:49:21.669870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:21.987706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 191
83.4%
영업 38
 
16.6%

폐업일자
Date

MISSING 

Distinct156
Distinct (%)81.7%
Missing38
Missing (%)16.6%
Memory size1.9 KiB
Minimum1988-10-19 00:00:00
Maximum2023-04-18 00:00:00
2024-05-11T08:49:22.440517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:49:22.925851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

전화번호
Text

MISSING 

Distinct159
Distinct (%)76.4%
Missing21
Missing (%)9.2%
Memory size1.9 KiB
2024-05-11T08:49:23.988458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.105769
Min length6

Characters and Unicode

Total characters2102
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)68.3%

Sample

1st row02 00000
2nd row02 00000
3rd row02 4793108
4th row02 4222667
5th row02 4229725
ValueCountFrequency (%)
02 164
42.5%
00000 18
 
4.7%
0200000000 17
 
4.4%
4197000 3
 
0.8%
4076117 2
 
0.5%
419 2
 
0.5%
4008841 2
 
0.5%
4001309 2
 
0.5%
4068819 2
 
0.5%
4150004 2
 
0.5%
Other values (161) 172
44.6%
2024-05-11T08:49:25.602837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 600
28.5%
2 334
15.9%
4 267
12.7%
236
 
11.2%
1 144
 
6.9%
3 116
 
5.5%
5 93
 
4.4%
8 89
 
4.2%
9 78
 
3.7%
7 77
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1866
88.8%
Space Separator 236
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 600
32.2%
2 334
17.9%
4 267
14.3%
1 144
 
7.7%
3 116
 
6.2%
5 93
 
5.0%
8 89
 
4.8%
9 78
 
4.2%
7 77
 
4.1%
6 68
 
3.6%
Space Separator
ValueCountFrequency (%)
236
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2102
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 600
28.5%
2 334
15.9%
4 267
12.7%
236
 
11.2%
1 144
 
6.9%
3 116
 
5.5%
5 93
 
4.4%
8 89
 
4.2%
9 78
 
3.7%
7 77
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 600
28.5%
2 334
15.9%
4 267
12.7%
236
 
11.2%
1 144
 
6.9%
3 116
 
5.5%
5 93
 
4.4%
8 89
 
4.2%
9 78
 
3.7%
7 77
 
3.7%
Distinct165
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-11T08:49:26.994584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.4323144
Min length3

Characters and Unicode

Total characters1244
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)67.7%

Sample

1st row107.98
2nd row310.38
3rd row.00
4th row.00
5th row.00
ValueCountFrequency (%)
00 56
 
24.5%
396.00 2
 
0.9%
266.40 2
 
0.9%
368.28 2
 
0.9%
163.00 2
 
0.9%
432.90 2
 
0.9%
660.00 2
 
0.9%
733.70 2
 
0.9%
495.00 2
 
0.9%
792.00 2
 
0.9%
Other values (155) 155
67.7%
2024-05-11T08:49:28.354482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 302
24.3%
. 229
18.4%
6 92
 
7.4%
2 86
 
6.9%
4 83
 
6.7%
3 78
 
6.3%
1 78
 
6.3%
5 76
 
6.1%
8 69
 
5.5%
9 66
 
5.3%
Other values (2) 85
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 995
80.0%
Other Punctuation 249
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 302
30.4%
6 92
 
9.2%
2 86
 
8.6%
4 83
 
8.3%
3 78
 
7.8%
1 78
 
7.8%
5 76
 
7.6%
8 69
 
6.9%
9 66
 
6.6%
7 65
 
6.5%
Other Punctuation
ValueCountFrequency (%)
. 229
92.0%
, 20
 
8.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1244
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 302
24.3%
. 229
18.4%
6 92
 
7.4%
2 86
 
6.9%
4 83
 
6.7%
3 78
 
6.3%
1 78
 
6.3%
5 76
 
6.1%
8 69
 
5.5%
9 66
 
5.3%
Other values (2) 85
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1244
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 302
24.3%
. 229
18.4%
6 92
 
7.4%
2 86
 
6.9%
4 83
 
6.7%
3 78
 
6.3%
1 78
 
6.3%
5 76
 
6.1%
8 69
 
5.5%
9 66
 
5.3%
Other values (2) 85
 
6.8%
Distinct83
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-11T08:49:28.973243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0305677
Min length6

Characters and Unicode

Total characters1381
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)17.0%

Sample

1st row138210
2nd row138210
3rd row138210
4th row138210
5th row138911
ValueCountFrequency (%)
138210 60
26.2%
138828 8
 
3.5%
138862 6
 
2.6%
138805 5
 
2.2%
138855 5
 
2.2%
138200 5
 
2.2%
138849 4
 
1.7%
138934 4
 
1.7%
138827 4
 
1.7%
138825 4
 
1.7%
Other values (73) 124
54.1%
2024-05-11T08:49:30.154670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 390
28.2%
1 328
23.8%
3 266
19.3%
2 115
 
8.3%
0 108
 
7.8%
5 48
 
3.5%
4 42
 
3.0%
6 28
 
2.0%
7 28
 
2.0%
9 21
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1374
99.5%
Dash Punctuation 7
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 390
28.4%
1 328
23.9%
3 266
19.4%
2 115
 
8.4%
0 108
 
7.9%
5 48
 
3.5%
4 42
 
3.1%
6 28
 
2.0%
7 28
 
2.0%
9 21
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1381
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 390
28.2%
1 328
23.8%
3 266
19.3%
2 115
 
8.3%
0 108
 
7.8%
5 48
 
3.5%
4 42
 
3.0%
6 28
 
2.0%
7 28
 
2.0%
9 21
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1381
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 390
28.2%
1 328
23.8%
3 266
19.3%
2 115
 
8.3%
0 108
 
7.8%
5 48
 
3.5%
4 42
 
3.0%
6 28
 
2.0%
7 28
 
2.0%
9 21
 
1.5%
Distinct210
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-11T08:49:30.798939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35
Mean length23.585153
Min length16

Characters and Unicode

Total characters5401
Distinct characters112
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique192 ?
Unique (%)83.8%

Sample

1st row서울특별시 송파구 장지동 산 94-15번지
2nd row서울특별시 송파구 장지동 산 129-2번지
3rd row서울특별시 송파구 장지동 산 227-4번지
4th row서울특별시 송파구 장지동 산 19-3번지
5th row서울특별시 송파구 잠실동 22-6번지 2단지상가
ValueCountFrequency (%)
서울특별시 229
21.7%
송파구 229
21.7%
장지동 61
 
5.8%
61
 
5.8%
방이동 28
 
2.7%
가락동 27
 
2.6%
잠실동 26
 
2.5%
문정동 17
 
1.6%
지하1층 14
 
1.3%
송파동 13
 
1.2%
Other values (234) 349
33.1%
2024-05-11T08:49:31.720168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1038
19.2%
304
 
5.6%
247
 
4.6%
242
 
4.5%
238
 
4.4%
230
 
4.3%
230
 
4.3%
229
 
4.2%
229
 
4.2%
229
 
4.2%
Other values (102) 2185
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3284
60.8%
Space Separator 1038
 
19.2%
Decimal Number 867
 
16.1%
Dash Punctuation 195
 
3.6%
Other Punctuation 5
 
0.1%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
304
 
9.3%
247
 
7.5%
242
 
7.4%
238
 
7.2%
230
 
7.0%
230
 
7.0%
229
 
7.0%
229
 
7.0%
229
 
7.0%
229
 
7.0%
Other values (85) 877
26.7%
Decimal Number
ValueCountFrequency (%)
1 213
24.6%
2 153
17.6%
0 79
 
9.1%
4 76
 
8.8%
3 72
 
8.3%
5 64
 
7.4%
7 58
 
6.7%
9 56
 
6.5%
6 50
 
5.8%
8 46
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 3
75.0%
F 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1038
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 195
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3284
60.8%
Common 2113
39.1%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
304
 
9.3%
247
 
7.5%
242
 
7.4%
238
 
7.2%
230
 
7.0%
230
 
7.0%
229
 
7.0%
229
 
7.0%
229
 
7.0%
229
 
7.0%
Other values (85) 877
26.7%
Common
ValueCountFrequency (%)
1038
49.1%
1 213
 
10.1%
- 195
 
9.2%
2 153
 
7.2%
0 79
 
3.7%
4 76
 
3.6%
3 72
 
3.4%
5 64
 
3.0%
7 58
 
2.7%
9 56
 
2.7%
Other values (5) 109
 
5.2%
Latin
ValueCountFrequency (%)
B 3
75.0%
F 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3284
60.8%
ASCII 2117
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1038
49.0%
1 213
 
10.1%
- 195
 
9.2%
2 153
 
7.2%
0 79
 
3.7%
4 76
 
3.6%
3 72
 
3.4%
5 64
 
3.0%
7 58
 
2.7%
9 56
 
2.6%
Other values (7) 113
 
5.3%
Hangul
ValueCountFrequency (%)
304
 
9.3%
247
 
7.5%
242
 
7.4%
238
 
7.2%
230
 
7.0%
230
 
7.0%
229
 
7.0%
229
 
7.0%
229
 
7.0%
229
 
7.0%
Other values (85) 877
26.7%

도로명주소
Text

MISSING 

Distinct73
Distinct (%)100.0%
Missing156
Missing (%)68.1%
Memory size1.9 KiB
2024-05-11T08:49:32.301739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length29.876712
Min length22

Characters and Unicode

Total characters2181
Distinct characters121
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)100.0%

Sample

1st row서울특별시 송파구 송파대로 359 (가락동, 가락시영아파트상가)
2nd row서울특별시 송파구 백제고분로39길 13 (석촌동)
3rd row서울특별시 송파구 가락로 71 (석촌동)
4th row서울특별시 송파구 마천로 250 (거여동)
5th row서울특별시 송파구 올림픽로32길 21-10, 지하1층 (방이동)
ValueCountFrequency (%)
서울특별시 73
 
17.3%
송파구 73
 
17.3%
지하1층 12
 
2.8%
방이동 10
 
2.4%
가락동 10
 
2.4%
잠실동 9
 
2.1%
문정동 8
 
1.9%
가락로 7
 
1.7%
석촌동 7
 
1.7%
올림픽로 6
 
1.4%
Other values (152) 207
49.1%
2024-05-11T08:49:33.287605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
349
 
16.0%
91
 
4.2%
88
 
4.0%
85
 
3.9%
1 76
 
3.5%
75
 
3.4%
74
 
3.4%
( 74
 
3.4%
) 74
 
3.4%
74
 
3.4%
Other values (111) 1121
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1323
60.7%
Space Separator 349
 
16.0%
Decimal Number 296
 
13.6%
Open Punctuation 74
 
3.4%
Close Punctuation 74
 
3.4%
Other Punctuation 51
 
2.3%
Dash Punctuation 8
 
0.4%
Uppercase Letter 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
91
 
6.9%
88
 
6.7%
85
 
6.4%
75
 
5.7%
74
 
5.6%
74
 
5.6%
73
 
5.5%
73
 
5.5%
73
 
5.5%
73
 
5.5%
Other values (92) 544
41.1%
Decimal Number
ValueCountFrequency (%)
1 76
25.7%
2 54
18.2%
3 37
12.5%
0 26
 
8.8%
5 21
 
7.1%
8 20
 
6.8%
6 19
 
6.4%
4 18
 
6.1%
9 13
 
4.4%
7 12
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
S 2
33.3%
B 2
33.3%
F 1
16.7%
J 1
16.7%
Space Separator
ValueCountFrequency (%)
349
100.0%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Other Punctuation
ValueCountFrequency (%)
, 51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1323
60.7%
Common 852
39.1%
Latin 6
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
91
 
6.9%
88
 
6.7%
85
 
6.4%
75
 
5.7%
74
 
5.6%
74
 
5.6%
73
 
5.5%
73
 
5.5%
73
 
5.5%
73
 
5.5%
Other values (92) 544
41.1%
Common
ValueCountFrequency (%)
349
41.0%
1 76
 
8.9%
( 74
 
8.7%
) 74
 
8.7%
2 54
 
6.3%
, 51
 
6.0%
3 37
 
4.3%
0 26
 
3.1%
5 21
 
2.5%
8 20
 
2.3%
Other values (5) 70
 
8.2%
Latin
ValueCountFrequency (%)
S 2
33.3%
B 2
33.3%
F 1
16.7%
J 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1323
60.7%
ASCII 858
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
349
40.7%
1 76
 
8.9%
( 74
 
8.6%
) 74
 
8.6%
2 54
 
6.3%
, 51
 
5.9%
3 37
 
4.3%
0 26
 
3.0%
5 21
 
2.4%
8 20
 
2.3%
Other values (9) 76
 
8.9%
Hangul
ValueCountFrequency (%)
91
 
6.9%
88
 
6.7%
85
 
6.4%
75
 
5.7%
74
 
5.6%
74
 
5.6%
73
 
5.5%
73
 
5.5%
73
 
5.5%
73
 
5.5%
Other values (92) 544
41.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct59
Distinct (%)83.1%
Missing158
Missing (%)69.0%
Infinite0
Infinite (%)0.0%
Mean5659.6056
Minimum5510
Maximum5840
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T08:49:33.709721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5510
5-th percentile5532
Q15565
median5652
Q35742.5
95-th percentile5828
Maximum5840
Range330
Interquartile range (IQR)177.5

Descriptive statistics

Standard deviation99.398114
Coefficient of variation (CV)0.017562728
Kurtosis-1.171081
Mean5659.6056
Median Absolute Deviation (MAD)88
Skewness0.24627328
Sum401832
Variance9879.9851
MonotonicityNot monotonic
2024-05-11T08:49:34.240948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5510 3
 
1.3%
5554 3
 
1.3%
5711 2
 
0.9%
5768 2
 
0.9%
5644 2
 
0.9%
5719 2
 
0.9%
5543 2
 
0.9%
5547 2
 
0.9%
5803 2
 
0.9%
5718 2
 
0.9%
Other values (49) 49
 
21.4%
(Missing) 158
69.0%
ValueCountFrequency (%)
5510 3
1.3%
5528 1
 
0.4%
5536 1
 
0.4%
5537 1
 
0.4%
5540 1
 
0.4%
5542 1
 
0.4%
5543 2
0.9%
5547 2
0.9%
5554 3
1.3%
5556 1
 
0.4%
ValueCountFrequency (%)
5840 1
0.4%
5839 1
0.4%
5837 1
0.4%
5833 1
0.4%
5823 1
0.4%
5807 1
0.4%
5804 1
0.4%
5803 2
0.9%
5793 1
0.4%
5783 1
0.4%
Distinct207
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-11T08:49:34.898029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length5.3580786
Min length2

Characters and Unicode

Total characters1227
Distinct characters216
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique188 ?
Unique (%)82.1%

Sample

1st row조호목욕탕
2nd row태성탕
3rd row삼정탕
4th row일단지목욕탕
5th row강남온천탕
ValueCountFrequency (%)
사우나 5
 
2.0%
백우목욕탕 4
 
1.6%
잠실목욕탕 3
 
1.2%
산소사우나 2
 
0.8%
한증막 2
 
0.8%
가락 2
 
0.8%
한양탕 2
 
0.8%
갑을탕 2
 
0.8%
현대목욕탕 2
 
0.8%
설악 2
 
0.8%
Other values (213) 226
89.7%
2024-05-11T08:49:35.973401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
 
9.5%
64
 
5.2%
60
 
4.9%
56
 
4.6%
41
 
3.3%
41
 
3.3%
30
 
2.4%
29
 
2.4%
26
 
2.1%
23
 
1.9%
Other values (206) 741
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1176
95.8%
Space Separator 23
 
1.9%
Decimal Number 9
 
0.7%
Close Punctuation 7
 
0.6%
Open Punctuation 7
 
0.6%
Uppercase Letter 3
 
0.2%
Lowercase Letter 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
116
 
9.9%
64
 
5.4%
60
 
5.1%
56
 
4.8%
41
 
3.5%
41
 
3.5%
30
 
2.6%
29
 
2.5%
26
 
2.2%
23
 
2.0%
Other values (194) 690
58.7%
Decimal Number
ValueCountFrequency (%)
2 4
44.4%
5 2
22.2%
4 2
22.2%
1 1
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
S 1
33.3%
Y 1
33.3%
Space Separator
ValueCountFrequency (%)
23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
z 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1176
95.8%
Common 47
 
3.8%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
116
 
9.9%
64
 
5.4%
60
 
5.1%
56
 
4.8%
41
 
3.5%
41
 
3.5%
30
 
2.6%
29
 
2.5%
26
 
2.2%
23
 
2.0%
Other values (194) 690
58.7%
Common
ValueCountFrequency (%)
23
48.9%
) 7
 
14.9%
( 7
 
14.9%
2 4
 
8.5%
5 2
 
4.3%
4 2
 
4.3%
1 1
 
2.1%
& 1
 
2.1%
Latin
ValueCountFrequency (%)
C 1
25.0%
z 1
25.0%
S 1
25.0%
Y 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1176
95.8%
ASCII 51
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
116
 
9.9%
64
 
5.4%
60
 
5.1%
56
 
4.8%
41
 
3.5%
41
 
3.5%
30
 
2.6%
29
 
2.5%
26
 
2.2%
23
 
2.0%
Other values (194) 690
58.7%
ASCII
ValueCountFrequency (%)
23
45.1%
) 7
 
13.7%
( 7
 
13.7%
2 4
 
7.8%
5 2
 
3.9%
4 2
 
3.9%
C 1
 
2.0%
1 1
 
2.0%
z 1
 
2.0%
& 1
 
2.0%
Other values (2) 2
 
3.9%
Distinct130
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1999-07-09 00:00:00
Maximum2023-10-11 14:48:41
2024-05-11T08:49:36.353855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:49:36.857579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
I
190 
U
39 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowI
3rd rowI
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 190
83.0%
U 39
 
17.0%

Length

2024-05-11T08:49:37.275710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:37.566720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 190
83.0%
u 39
 
17.0%

데이터갱신일자
Categorical

IMBALANCE 

Distinct41
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2018-08-31 23:59:59.0
188 
2022-12-08 22:03:00.0
 
2
2021-12-05 22:04:00.0
 
1
2022-12-03 22:00:00.0
 
1
2018-12-30 02:40:00.0
 
1
Other values (36)
36 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique39 ?
Unique (%)17.0%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 188
82.1%
2022-12-08 22:03:00.0 2
 
0.9%
2021-12-05 22:04:00.0 1
 
0.4%
2022-12-03 22:00:00.0 1
 
0.4%
2018-12-30 02:40:00.0 1
 
0.4%
2021-05-02 02:40:00.0 1
 
0.4%
2018-12-20 02:40:00.0 1
 
0.4%
2019-09-25 02:40:00.0 1
 
0.4%
2021-06-17 02:40:00.0 1
 
0.4%
2020-06-11 02:40:00.0 1
 
0.4%
Other values (31) 31
 
13.5%

Length

2024-05-11T08:49:37.949970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 188
41.0%
23:59:59.0 188
41.0%
02:40:00.0 24
 
5.2%
22:03:00.0 3
 
0.7%
2022-12-08 2
 
0.4%
2021-12-05 2
 
0.4%
23:03:00.0 2
 
0.4%
2021-10-31 2
 
0.4%
2022-12-06 1
 
0.2%
2020-03-20 1
 
0.2%
Other values (45) 45
 
9.8%

업태구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
공동탕업
203 
목욕장업 기타
 
9
공동탕업+찜질시설서비스영업
 
8
한증막업
 
6
찜질시설서비스영업
 
3

Length

Max length14
Median length4
Mean length4.5327511
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공동탕업
2nd row공동탕업
3rd row공동탕업
4th row공동탕업
5th row공동탕업

Common Values

ValueCountFrequency (%)
공동탕업 203
88.6%
목욕장업 기타 9
 
3.9%
공동탕업+찜질시설서비스영업 8
 
3.5%
한증막업 6
 
2.6%
찜질시설서비스영업 3
 
1.3%

Length

2024-05-11T08:49:38.352768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:38.734927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 203
85.3%
목욕장업 9
 
3.8%
기타 9
 
3.8%
공동탕업+찜질시설서비스영업 8
 
3.4%
한증막업 6
 
2.5%
찜질시설서비스영업 3
 
1.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct120
Distinct (%)75.5%
Missing70
Missing (%)30.6%
Infinite0
Infinite (%)0.0%
Mean209989.52
Minimum206731.19
Maximum213577.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T08:49:39.181300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206731.19
5-th percentile207051.99
Q1209016.58
median210057.91
Q3211017.7
95-th percentile212962.78
Maximum213577.58
Range6846.3917
Interquartile range (IQR)2001.1178

Descriptive statistics

Standard deviation1580.3148
Coefficient of variation (CV)0.0075256843
Kurtosis-0.21464374
Mean209989.52
Median Absolute Deviation (MAD)1016.8235
Skewness0.028488909
Sum33388334
Variance2497395
MonotonicityNot monotonic
2024-05-11T08:49:39.840888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208589.363343145 7
 
3.1%
211867.644806767 3
 
1.3%
211111.990469749 3
 
1.3%
206877.588291045 3
 
1.3%
208901.424566355 3
 
1.3%
210491.321883503 3
 
1.3%
210347.070743819 2
 
0.9%
207825.490238236 2
 
0.9%
209966.124550614 2
 
0.9%
208851.639893799 2
 
0.9%
Other values (110) 129
56.3%
(Missing) 70
30.6%
ValueCountFrequency (%)
206731.192156063 1
 
0.4%
206877.588291045 3
1.3%
206916.75835 1
 
0.4%
206968.768877487 1
 
0.4%
207006.591695429 2
0.9%
207057.038960946 1
 
0.4%
207288.776191557 1
 
0.4%
207307.809494696 1
 
0.4%
207355.730625263 1
 
0.4%
207385.656211696 1
 
0.4%
ValueCountFrequency (%)
213577.583827273 1
0.4%
213341.099860091 1
0.4%
213279.781081276 1
0.4%
213252.720434881 2
0.9%
213221.075176619 1
0.4%
213012.617500517 1
0.4%
213004.403339154 1
0.4%
212958.155 1
0.4%
212811.975075042 1
0.4%
212802.305371634 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct120
Distinct (%)75.5%
Missing70
Missing (%)30.6%
Infinite0
Infinite (%)0.0%
Mean444701.51
Minimum441833.16
Maximum448278.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T08:49:40.458682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441833.16
5-th percentile442848.91
Q1443729.56
median444846.63
Q3445455.9
95-th percentile446467.63
Maximum448278.81
Range6445.6508
Interquartile range (IQR)1726.3439

Descriptive statistics

Standard deviation1210.1442
Coefficient of variation (CV)0.0027212504
Kurtosis0.60471572
Mean444701.51
Median Absolute Deviation (MAD)756.30508
Skewness0.18540458
Sum70707540
Variance1464448.9
MonotonicityNot monotonic
2024-05-11T08:49:41.460014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445455.90405262 7
 
3.1%
443580.087192091 3
 
1.3%
442106.154785377 3
 
1.3%
444826.298967878 3
 
1.3%
444139.864447626 3
 
1.3%
443569.763243482 3
 
1.3%
443830.404153393 2
 
0.9%
444529.311294572 2
 
0.9%
446059.613892034 2
 
0.9%
444965.4232772 2
 
0.9%
Other values (110) 129
56.3%
(Missing) 70
30.6%
ValueCountFrequency (%)
441833.16323518 1
 
0.4%
442038.143247 1
 
0.4%
442053.227933005 1
 
0.4%
442106.154785377 3
1.3%
442480.543456524 1
 
0.4%
442806.234709764 1
 
0.4%
442853.653892969 2
0.9%
442861.084380975 2
0.9%
443075.872998689 1
 
0.4%
443128.998334934 1
 
0.4%
ValueCountFrequency (%)
448278.81403543 1
0.4%
448136.501473978 1
0.4%
448057.334926718 1
0.4%
447916.043934269 1
0.4%
447471.180557382 1
0.4%
447414.523518115 1
0.4%
446708.866138582 1
0.4%
446691.34604437 1
0.4%
446442.771540314 1
0.4%
446059.613892034 2
0.9%

위생업태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
공동탕업
193 
<NA>
 
14
목욕장업 기타
 
8
한증막업
 
6
공동탕업+찜질시설서비스영업
 
6

Length

Max length14
Median length4
Mean length4.4104803
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공동탕업
2nd row공동탕업
3rd row공동탕업
4th row공동탕업
5th row공동탕업

Common Values

ValueCountFrequency (%)
공동탕업 193
84.3%
<NA> 14
 
6.1%
목욕장업 기타 8
 
3.5%
한증막업 6
 
2.6%
공동탕업+찜질시설서비스영업 6
 
2.6%
찜질시설서비스영업 2
 
0.9%

Length

2024-05-11T08:49:42.101421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:42.527464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 193
81.4%
na 14
 
5.9%
목욕장업 8
 
3.4%
기타 8
 
3.4%
한증막업 6
 
2.5%
공동탕업+찜질시설서비스영업 6
 
2.5%
찜질시설서비스영업 2
 
0.8%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)6.9%
Missing113
Missing (%)49.3%
Infinite0
Infinite (%)0.0%
Mean0.77586207
Minimum0
Maximum18
Zeros100
Zeros (%)43.7%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T08:49:42.886688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.6542377
Coefficient of variation (CV)3.4210174
Kurtosis29.885653
Mean0.77586207
Median Absolute Deviation (MAD)0
Skewness5.1038677
Sum90
Variance7.0449775
MonotonicityNot monotonic
2024-05-11T08:49:43.341417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 100
43.7%
4 4
 
1.7%
5 4
 
1.7%
3 3
 
1.3%
18 2
 
0.9%
6 1
 
0.4%
2 1
 
0.4%
1 1
 
0.4%
(Missing) 113
49.3%
ValueCountFrequency (%)
0 100
43.7%
1 1
 
0.4%
2 1
 
0.4%
3 3
 
1.3%
4 4
 
1.7%
5 4
 
1.7%
6 1
 
0.4%
18 2
 
0.9%
ValueCountFrequency (%)
18 2
 
0.9%
6 1
 
0.4%
5 4
 
1.7%
4 4
 
1.7%
3 3
 
1.3%
2 1
 
0.4%
1 1
 
0.4%
0 100
43.7%
Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
115 
0
98 
1
 
9
2
 
4
5
 
2

Length

Max length4
Median length4
Mean length2.5065502
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 115
50.2%
0 98
42.8%
1 9
 
3.9%
2 4
 
1.7%
5 2
 
0.9%
4 1
 
0.4%

Length

2024-05-11T08:49:44.157926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:44.635659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 115
50.2%
0 98
42.8%
1 9
 
3.9%
2 4
 
1.7%
5 2
 
0.9%
4 1
 
0.4%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)6.1%
Missing130
Missing (%)56.8%
Infinite0
Infinite (%)0.0%
Mean0.42424242
Minimum0
Maximum13
Zeros84
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T08:49:45.129722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5524234
Coefficient of variation (CV)3.6592838
Kurtosis45.40524
Mean0.42424242
Median Absolute Deviation (MAD)0
Skewness6.1568935
Sum42
Variance2.4100186
MonotonicityNot monotonic
2024-05-11T08:49:45.602689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 84
36.7%
1 6
 
2.6%
2 5
 
2.2%
5 2
 
0.9%
3 1
 
0.4%
13 1
 
0.4%
(Missing) 130
56.8%
ValueCountFrequency (%)
0 84
36.7%
1 6
 
2.6%
2 5
 
2.2%
3 1
 
0.4%
5 2
 
0.9%
13 1
 
0.4%
ValueCountFrequency (%)
13 1
 
0.4%
5 2
 
0.9%
3 1
 
0.4%
2 5
 
2.2%
1 6
 
2.6%
0 84
36.7%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)25.0%
Missing205
Missing (%)89.5%
Infinite0
Infinite (%)0.0%
Mean1.8333333
Minimum0
Maximum13
Zeros9
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T08:49:46.053983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum13
Range13
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.8078565
Coefficient of variation (CV)1.5315581
Kurtosis10.970145
Mean1.8333333
Median Absolute Deviation (MAD)1
Skewness3.0012713
Sum44
Variance7.884058
MonotonicityNot monotonic
2024-05-11T08:49:46.416494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 9
 
3.9%
1 5
 
2.2%
2 5
 
2.2%
3 2
 
0.9%
5 2
 
0.9%
13 1
 
0.4%
(Missing) 205
89.5%
ValueCountFrequency (%)
0 9
3.9%
1 5
2.2%
2 5
2.2%
3 2
 
0.9%
5 2
 
0.9%
13 1
 
0.4%
ValueCountFrequency (%)
13 1
 
0.4%
5 2
 
0.9%
3 2
 
0.9%
2 5
2.2%
1 5
2.2%
0 9
3.9%
Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
123 
0
85 
1
21 

Length

Max length4
Median length4
Mean length2.6113537
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 123
53.7%
0 85
37.1%
1 21
 
9.2%

Length

2024-05-11T08:49:46.816926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:47.238192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 123
53.7%
0 85
37.1%
1 21
 
9.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
198 
1
 
17
0
 
10
2
 
4

Length

Max length4
Median length4
Mean length3.5938865
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 198
86.5%
1 17
 
7.4%
0 10
 
4.4%
2 4
 
1.7%

Length

2024-05-11T08:49:47.593704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:47.925423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 198
86.5%
1 17
 
7.4%
0 10
 
4.4%
2 4
 
1.7%

한실수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
125 
0
104 

Length

Max length4
Median length4
Mean length2.6375546
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 125
54.6%
0 104
45.4%

Length

2024-05-11T08:49:48.420396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:48.889851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
54.6%
0 104
45.4%

양실수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
125 
0
104 

Length

Max length4
Median length4
Mean length2.6375546
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 125
54.6%
0 104
45.4%

Length

2024-05-11T08:49:49.436787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:50.009980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
54.6%
0 104
45.4%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)6.5%
Missing121
Missing (%)52.8%
Infinite0
Infinite (%)0.0%
Mean0.67592593
Minimum0
Maximum16
Zeros84
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T08:49:50.372196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.65
Maximum16
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.947098
Coefficient of variation (CV)2.8806382
Kurtosis36.796085
Mean0.67592593
Median Absolute Deviation (MAD)0
Skewness5.3520591
Sum73
Variance3.7911907
MonotonicityNot monotonic
2024-05-11T08:49:50.792134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 84
36.7%
2 13
 
5.7%
1 5
 
2.2%
6 3
 
1.3%
5 1
 
0.4%
16 1
 
0.4%
3 1
 
0.4%
(Missing) 121
52.8%
ValueCountFrequency (%)
0 84
36.7%
1 5
 
2.2%
2 13
 
5.7%
3 1
 
0.4%
5 1
 
0.4%
6 3
 
1.3%
16 1
 
0.4%
ValueCountFrequency (%)
16 1
 
0.4%
6 3
 
1.3%
5 1
 
0.4%
3 1
 
0.4%
2 13
 
5.7%
1 5
 
2.2%
0 84
36.7%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.9%
Missing14
Missing (%)6.1%
Memory size590.0 B
False
202 
True
 
13
(Missing)
 
14
ValueCountFrequency (%)
False 202
88.2%
True 13
 
5.7%
(Missing) 14
 
6.1%
2024-05-11T08:49:51.217618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
123 
0
104 
5
 
1
7
 
1

Length

Max length4
Median length4
Mean length2.6113537
Min length1

Unique

Unique2 ?
Unique (%)0.9%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 123
53.7%
0 104
45.4%
5 1
 
0.4%
7 1
 
0.4%

Length

2024-05-11T08:49:51.666758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:52.011366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 123
53.7%
0 104
45.4%
5 1
 
0.4%
7 1
 
0.4%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
218 
임대
 
6
자가
 
5

Length

Max length4
Median length4
Mean length3.9039301
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 218
95.2%
임대 6
 
2.6%
자가 5
 
2.2%

Length

2024-05-11T08:49:52.498031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:52.852691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 218
95.2%
임대 6
 
2.6%
자가 5
 
2.2%

세탁기수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
200 
0
29 

Length

Max length4
Median length4
Mean length3.6200873
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 200
87.3%
0 29
 
12.7%

Length

2024-05-11T08:49:53.303035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:53.727245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
87.3%
0 29
 
12.7%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
220 
0
 
9

Length

Max length4
Median length4
Mean length3.8820961
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 220
96.1%
0 9
 
3.9%

Length

2024-05-11T08:49:54.077125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:54.591820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 220
96.1%
0 9
 
3.9%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
220 
0
 
7
1
 
2

Length

Max length4
Median length4
Mean length3.8820961
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 220
96.1%
0 7
 
3.1%
1 2
 
0.9%

Length

2024-05-11T08:49:54.960312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:55.332960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 220
96.1%
0 7
 
3.1%
1 2
 
0.9%

회수건조수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
205 
0
24 

Length

Max length4
Median length4
Mean length3.6855895
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 205
89.5%
0 24
 
10.5%

Length

2024-05-11T08:49:55.726600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:56.161150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 205
89.5%
0 24
 
10.5%

침대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
207 
0
22 

Length

Max length4
Median length4
Mean length3.7117904
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 207
90.4%
0 22
 
9.6%

Length

2024-05-11T08:49:56.514578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:49:56.834464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 207
90.4%
0 22
 
9.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing14
Missing (%)6.1%
Memory size590.0 B
False
215 
(Missing)
 
14
ValueCountFrequency (%)
False 215
93.9%
(Missing) 14
 
6.1%
2024-05-11T08:49:57.148886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032300003230000-202-1969-0022319690919<NA>3폐업2폐업19960612<NA><NA><NA>02 00000107.98138210서울특별시 송파구 장지동 산 94-15번지<NA><NA>조호목욕탕2002-09-04 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132300003230000-202-1973-0022419730601<NA>3폐업2폐업19990630<NA><NA><NA>02 00000310.38138210서울특별시 송파구 장지동 산 129-2번지<NA><NA>태성탕2002-09-04 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232300003230000-202-1976-0022219761227<NA>3폐업2폐업20030227<NA><NA><NA>02 4793108.00138210서울특별시 송파구 장지동 산 227-4번지<NA><NA>삼정탕2003-03-11 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
332300003230000-202-1976-0022519760713<NA>3폐업2폐업20030227<NA><NA><NA>02 4222667.00138210서울특별시 송파구 장지동 산 19-3번지<NA><NA>일단지목욕탕2000-03-31 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432300003230000-202-1976-0022620030227<NA>3폐업2폐업20040129<NA><NA><NA>02 4229725.00138911서울특별시 송파구 잠실동 22-6번지 2단지상가<NA><NA>강남온천탕2003-06-13 00:00:00I2018-08-31 23:59:59.0공동탕업207624.424721445533.439634공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
532300003230000-202-1976-0022719760325<NA>3폐업2폐업20030227<NA><NA><NA>02 4136981301.94138210서울특별시 송파구 장지동 산 35-2번지<NA><NA>삼단지목욕탕2002-09-04 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632300003230000-202-1976-0022819760322<NA>3폐업2폐업20030227<NA><NA><NA>02 4223195294.76138210서울특별시 송파구 장지동 산 44-0번지<NA><NA>잠실목욕탕2002-09-04 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732300003230000-202-1976-0022919760410<NA>3폐업2폐업20030101<NA><NA><NA>02 4189302268.66138210서울특별시 송파구 장지동 산 17-3번지<NA><NA>경화탕2003-04-12 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832300003230000-202-1976-0023019760512<NA>3폐업2폐업20030101<NA><NA><NA>02 4230609180.50138210서울특별시 송파구 장지동 산 13-4번지<NA><NA>성원탕2003-04-12 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
932300003230000-202-1979-0023119791231<NA>3폐업2폐업20030728<NA><NA><NA>02 4842645246.38138210서울특별시 송파구 장지동 산 17-0번지<NA><NA>장안탕2000-03-17 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
21932300003230000-202-2016-0000120160418<NA>3폐업2폐업20161208<NA><NA><NA>02 418 125312.00138834서울특별시 송파구 방이동 191-4번지서울특별시 송파구 위례성대로16길 14, 지상1층 (방이동)5637(주)자연숨2016-04-18 15:49:42I2018-08-31 23:59:59.0공동탕업210938.258591445500.352383공동탕업0011<NA><NA>001N0<NA><NA><NA><NA>00000N
22032300003230000-202-2016-0000220161005<NA>1영업/정상1영업<NA><NA><NA><NA>02 2043981160.00138803서울특별시 송파구 가락동 80번지서울특별시 송파구 송파대로28길 27, 지하1층 (가락동)5718주식회사 잠실투엑스휘트니스2018-01-24 14:49:10I2018-08-31 23:59:59.0목욕장업 기타210580.683291443657.712046목욕장업 기타00<NA><NA>11001N0<NA><NA><NA><NA>00000N
22132300003230000-202-2016-0000320161107<NA>3폐업2폐업20220330<NA><NA><NA>02 64252000183.00138805서울특별시 송파구 가락동 98-5서울특별시 송파구 송파대로28길 5, 지하1층 (가락동)5719가락 사우나2022-03-30 15:35:08U2021-12-04 00:01:00.0공동탕업210429.157119443526.648866<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22232300003230000-202-2017-0000120170105<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2,531.00138888서울특별시 송파구 문정동 618번지서울특별시 송파구 송파대로 111, 202동 101호 (문정동, 하비오길동 광장로)5837워터킹덤 워터파크 & 스파2018-11-20 17:38:28U2018-11-22 02:37:53.0공동탕업+찜질시설서비스영업210868.397497442053.227933공동탕업+찜질시설서비스영업0011<NA><NA>002Y0<NA><NA><NA><NA>00000N
22332300003230000-202-2017-0000220170206<NA>3폐업2폐업20191219<NA><NA><NA><NA>163.00138827서울특별시 송파구 방이동 36-1번지서울특별시 송파구 올림픽로32길 5, 2층 (방이동)5543제트(z) 사우나2019-12-19 10:49:18U2019-12-21 02:40:00.0공동탕업209568.188973445934.229165공동탕업002200002N0<NA><NA><NA><NA>00100N
22432300003230000-202-2017-0000320170727<NA>1영업/정상1영업<NA><NA><NA><NA><NA>390.00138861서울특별시 송파구 잠실동 175-6번지서울특별시 송파구 올림픽로 76, 13층 (잠실동, J 타워)5556피트니스 비엠2017-07-27 12:40:40I2018-08-31 23:59:59.0목욕장업 기타206916.75835445485.444774목욕장업 기타001313<NA><NA>002N0<NA><NA><NA><NA>00100N
22532300003230000-202-2018-0000120181123<NA>3폐업2폐업20221209<NA><NA><NA><NA>11.50138825서울특별시 송파구 문정동 29-24서울특별시 송파구 동남로 110, 5층 (문정동)5804슈나이더짐2022-12-09 15:10:19U2021-11-01 23:01:00.0찜질시설서비스영업210878.515429443075.872999<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22632300003230000-202-2020-0000120200611<NA>1영업/정상1영업<NA><NA><NA><NA>02 430 9864636.44138715서울특별시 송파구 가락동 99-3번지 제일오피스텔서울특별시 송파구 송파대로 260, 제일오피스텔 지하2층 (가락동)5719유어짐 가락2020-06-11 15:05:25I2020-06-13 00:23:18.0공동탕업210431.832858443465.459232공동탕업0022<NA><NA>006N0<NA><NA><NA>임대00000N
22732300003230000-202-2022-000012022-03-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>316.90138-721서울특별시 송파구 잠실동 40-1 롯데월드서울특별시 송파구 올림픽로 240, 5층 (잠실동)5554롯데호텔 여성사우나2023-09-21 09:41:55U2022-12-08 22:03:00.0목욕장업 기타208589.363343445455.904053<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22832300003230000-202-2023-000012023-02-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>175.68138-824서울특별시 송파구 문정동 21서울특별시 송파구 송이로32길 26, 지층 (문정동)5803양파한증막2023-02-06 15:14:13I2022-12-02 00:08:00.0공동탕업211175.631035442853.653893<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>